1353-P: Asymptomatic Individuals with β-Thalassemia Trait in Southern China Having Falsely Low Hemoglobin A1c Levels Are Readily Identified by Their Low MCV, Low MCH, and High RDW Values
Bibliographic record
Abstract
Introduction and Objective: Testing HbA1c in undiagnosed asymptomatic thalassemia traits/carriers in prevalent regions can be problematic because HbA1c values may falsely be altered, potentially leading to inappropriate management. Methods: This cross-sectional study evaluated 397 individuals who underwent annual health screening and thalassemia genetic testing in a tertiary care hospital. Of this cohort, 85 iron-deficient and 16 dysglycemic patients were excluded to avoid confounding the HbA1c levels. HbA1c was measured utilizing ion-exchange high-performance lipid chromatography (HPLC). Results: The most prevalent thalassemia in our cohort was α0-thalassemia (SEA deletion, 23%), followed by -α3.7/αα (6%) and heterozygous β mutations. Compared with 140 controls without detectable α and β mutations, patients with β-thalassemia trait and HbH disease had significantly lower HbA1c than controls, but the HbA1c in patients with silent α-thalassemia or α-thalassemia trait was comparable to controls. Among the red cell parameters, all β-thalassemia and HbH patients in our cohort had MCV <75 fL, MCH <24 pg, and RDW-CV >13.5%, distinctly lower than the controls, which helped to identify these patients even before the genetic confirmation. In contrast, although the red cell parameters of patients with silent α-thalassemia or α-thalassemia trait overlap with the normal controls, these α-thalassemia types did not affect the HbA1c levels. Conclusion: Misinterpretation of HbA1c levels can occur in patients with an undiagnosed β-thalassemia trait, readily identified by microcytosis, hypochromia, or an elevated RDW. In contrast, HbA1c levels in α-thalassemia carriers are generally unaffected when measured using HPLC, although these carriers might go unnoticed because their red blood cell parameters fall within the normal ranges. Disclosure L. Liu: None. M. Luo: None. I. Stevic: None. E.Y.S. Chan: None. A.K.C. Chan: Research Support; Canadian Institutes of Health Research. Other Relationship; Bayer Pharmaceuticals, Inc, Novo Nordisk. Research Support; C17 Network, Canadian Hemophilia Society. Other Relationship; Roche Pharmaceuticals, Pfizer Inc. Advisory Panel; Sanofi. Other Relationship; Takeda Pharmaceutical - Canada. Advisory Panel; OctaPharma. Other Relationship; McMaster University. H.H.W. Chan: Stock/Shareholder; Bristol-Myers Squibb Company. Funding Startup fund, the Chinese University of Hong Kong (Shenzhen)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".